Row

confirmed

4579

PCR tests

27864

Antibody Tests

21139

death

411

Row

Map

Daily cumulative cases

Row

Zipcode cases

Town cases

Row

Daily counts

Daily counts

date confirmed new active recovered deaths
62 2020-05-14 4579 0 NA NA 400
61 2020-05-13 4579 95 NA NA 400
60 2020-05-12 4484 0 NA NA 387
59 2020-05-11 4484 151 NA NA 387
58 2020-05-10 4333 0 NA NA 357
57 2020-05-09 4333 172 NA NA 357
56 2020-05-08 4161 222 NA NA 346
55 2020-05-07 3939 0 NA NA 323
54 2020-05-06 3939 190 NA NA 323
53 2020-05-05 3749 0 NA NA 308
52 2020-05-04 3749 268 NA NA 308
51 2020-05-03 3481 0 NA NA 283
50 2020-05-02 3481 0 NA NA 283
49 2020-05-01 3481 71 NA NA 283
48 2020-04-30 3410 95 NA NA 266
47 2020-04-29 3315 91 NA NA 254
46 2020-04-28 3224 163 NA NA 245
45 2020-04-27 3061 65 NA NA 207
44 2020-04-26 2996 139 NA NA 207
43 2020-04-25 2857 119 NA NA 207
42 2020-04-24 2738 144 NA NA 198
41 2020-04-23 2594 89 NA NA 188
40 2020-04-22 2505 221 NA NA 188
39 2020-04-21 2284 63 NA NA 177
38 2020-04-20 2221 29 NA NA 162
37 2020-04-19 2192 65 NA NA 135
36 2020-04-18 2127 104 NA NA 131
35 2020-04-17 2023 72 NA NA 115
34 2020-04-16 1951 139 NA NA 107
33 2020-04-15 1812 82 NA NA 104
32 2020-04-14 1730 69 1178 479 73
31 2020-04-13 1661 37 1116 479 66
30 2020-04-12 1624 66 1084 479 61
29 2020-04-11 1558 52 1071 430 57
28 2020-04-10 1506 66 1019 430 57
27 2020-04-09 1440 95 989 398 53
26 2020-04-08 1345 110 950 349 46
25 2020-04-07 1235 72 893 303 39
24 2020-04-06 1163 104 910 223 30
23 2020-04-05 1059 114 861 171 27
22 2020-04-04 945 143 758 161 26
21 2020-04-03 802 68 639 141 22
20 2020-04-02 734 131 614 101 19
19 2020-04-01 603 50 510 81 12
18 2020-03-31 553 90 481 62 10
17 2020-03-30 463 49 402 53 8
16 2020-03-29 414 34 375 32 7
15 2020-03-28 380 70 347 27 6
14 2020-03-27 310 89 277 27 6
13 2020-03-26 221 75 200 16 5
12 2020-03-25 146 25 139 5 2
11 2020-03-24 121 25 121 0 0
10 2020-03-23 96 32 96 0 0
9 2020-03-22 64 8 64 0 0
8 2020-03-21 56 9 56 0 0
7 2020-03-20 47 18 47 0 0
6 2020-03-19 29 2 29 0 0
5 2020-03-18 27 7 27 0 0
4 2020-03-17 20 13 20 0 0
3 2020-03-16 7 0 7 0 0
2 2020-03-15 7 4 7 0 0
1 2020-03-14 3 3 3 0 0
---
title: COVID19(Erie county)
date: "`r gsub('\\(updated |\\ EST)|/2020', '', attributes(Counts$counts)$update.time)`"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    navbar:
      - { icon: fa-github, href: "https://github.com/hubentu/COVID19Erie"}
      - { title: "Erie Case Map", href: "https://erieny.maps.arcgis.com/apps/opsdashboard/index.html#/dd7f1c0c352e4192ab162a1dfadc58e1"}
      - { title: "Global Map", href: "https://coronavirus.jhu.edu/map.html"}
    social: menu
    source_code: embed
    vertical_layout: scroll
---

```{r setup, include=FALSE}
library(flexdashboard)
library(fontawesome)
## library(COVID19Erie)
## pubExposed <- exposedPub()
```

```{r}
Counts <- caseCounts()
counts <- Counts$counts
ctable1 <- rbind(counts,
                c(town = "Total", colSums(counts[,-1])))
ycount <- historyCount$confirmed[historyCount$date == Sys.Date() - 1]
ncount <- attributes(counts)$total.confirmed - ycount
```

Row {data-width=300}
-----------------------------------------------------------------------

### confirmed {.value-box}

```{r}
valueBox(
  value = attributes(counts)$total.confirmed,
  caption = paste0("Total confirmed cases (+", ncount, ")"),
  icon = "fas fa-ambulance",
  color = "purple"
)
```

### PCR tests {.value-box}
```{r}
valueBox(
  value = attributes(counts)$PCR.tested,
  caption = "Total PCR (Swab) Tests",
  icon = "fas fa-hospital-user",
  color = "#1f77b4"
)
```

### Antibody Tests {.value-box}
```{r}
valueBox(
  value = attributes(counts)$Antibody.tested,
  caption = "Total Antibody Tests",
  icon = "fas fa-hospital-user",
  color = "forestgreen"
)
```












### death {.value-box}

```{r}
valueBox(
  value = attributes(counts)$total.deaths,
  caption = "Death cases",
  icon = "fas fa-heart-broken",
  color = "#474747"
)
```


Row {data-height=600}
-----------------------------------------------------------------------
    
### Map
    
```{r}
caseMap(Counts, pubExposed, titlePos = NULL)
```

### Daily cumulative cases
```{r}
countPlot(historyCount)
```

Row
---------------------------------------------------------------------

### Zipcode cases
```{r}
library(DT)
datatable(Counts$zipCounts, options = list(scrollX = T))
```

### Town cases

```{r}
## library(knitr)
## library(kableExtra)
## kable(ctable1,
##       caption = "COVID19 cases (Erie county)") %>%
##     kable_styling(full_width = TRUE) %>% 
##     footnote(general = c(paste("Last updated:", attributes(counts)$update.time),
##                          "[Data Source](https://erieny.maps.arcgis.com/apps/opsdashboard/index.html#/dd7f1c0c352e4192ab162a1dfadc58e1)",
##                          "[Public Advisories](http://www2.erie.gov/health/index.php?q=public-advisories)",
##                          "The data is only for educational and academic research purposes.")) %>%
## scroll_box(height = "600px")
datatable(ctable1[,1:2], options = list(scrollX = T))
```

Row
----------------------------------------------------------------------

### Daily counts {.no-mobile}
```{r}
datatable(historyCount[order(historyCount$date, decreasing = TRUE),],
          extensions = 'Scroller',
          options = list(scrollX = TRUE))
```

### Daily counts {.mobile}
```{r}
library(knitr)
library(kableExtra)
kable(historyCount[order(historyCount$date, decreasing = TRUE),]) %>%
    kable_styling(font_size = 8)%>%
    scroll_box(height = "600px", width = "100%")
```